Real-World Pharmacological Treatment Pattern of Neuropathic Pain in China: A Retrospective, Database, Multicenter Study (ReTARdant) Protocol.

Key Summary Points

Why carry out this study? The real-world evidence on demographic characteristics, treatment patterns, dosing pattern, and adherence data of neuropathic pain (NP) is still limited. As diabetic peripheral neuropathic pain (DPNP) and chemotherapy-induced peripheral neuropathy (CIPN) are the common types of NP, we carried out this study to explore the treatment pattern among these patients in China. What was learnt from this study? To our knowledge, this study is the first large-sample, multicenter, retrospective study to investigate the real-world treatment patterns and outcomes in Chinese patients with DPNP and CIPN observed between January 2018 and December 2022. This study will provide profound insights into clinical unmet needs of DPNP and CIPN, especially potential treatment gaps between clinical practice and guidelines in China, by evaluating the treatment patterns.

Introduction

Neuropathic pain (NP) is characterized by chronic pain caused by somatosensory system disease or damage [ 1 ]. Studies have shown that the prevalence of NP in the general population is about 7–10% [ 2 ], with approximately 90 million individuals in China affected by NP [ 3 ]. The most common and well-described types of NP are due to diabetes and chemotherapy [ 4 ]. Globally, the prevalence of diabetic peripheral neuropathic pain (DPNP) ranges from 3.3% to 65.3% [ 5 ]; in China, the estimated prevalence is 57.28% in patients with type 2 diabetes mellitus and diabetic peripheral neuropathy [ 6 ]. Chemotherapy-induced peripheral neuropathy (CIPN) prevalence ranges from 14.2% to 71.4%, influenced by factors such as the timing of assessment, the type of chemotherapy, and the assessment method used [ 7 ]. Few studies have reported the prevalence of CIPN in Chinese patients, ranging from 73.9% to 79.1% in patients with breast cancer and 69.3% in patients with ovarian cancer [ 8 – 10 ], as well as limited data on other cancer types.

First-line treatment for NP typically includes non-opioid medications such as tricyclic antidepressants (TCAs), serotonin–norepinephrine reuptake inhibitors (SNRIs), and gabapentinoids are recommended by guidelines. If ineffective, second-line treatment involves tramadol or tapentadol, with third-line treatments including serotonin-specific reuptake inhibitors, anticonvulsants, and N -methyl d -aspartate (NMDA) receptor antagonists [ 11 – 13 ]. In real-world practice, a cross-sectional study on mainland China (PDN-SCOPE) reported that 19.5% of patients with DPNP received prescriptions for relief from NP; of those, gabapentin was the most prescribed drug. Furthermore, 9.43% (33/350) of patients receiving non-steroidal anti-inflammatory drugs (NSAIDs), Chinese traditional medicine, and oxcarbazepine as first-line medication did not align with the guideline recommendations [ 14 ]. In another cross-sectional study, pregabalin was the first choice for Chinese patients with DPNP, followed by duloxetine and tapentadol. However, only 46.18% of the patients were satisfied with the efficacy, and 28% of patients believed that the treatment significantly reduced pain [ 15 ]. Studies assessing the treatment pattern and therapeutic effectiveness of CIPN were mostly conducted in the Western countries. A study conducted in the USA reported that 59% of the patients with CIPN treated with duloxetine showed a reduction in pain and significant improvements in the pain scores and quality of life (QoL) [ 16 ].

The dose titration is associated with improved treatment adherence and persistence in patients with NP. A MarketScan database study reported that patients with pregabalin dose titration were 2.6 times more adherent (medication possession ratio [MPR] ≥ 0.8; odds ratio [OR] .59; p < 0.001) and had greater persistence (median time to discontinuation/switch 5 months) than those without a dose titration (median time to discontinuation/switch 4 months) [ 17 ]. It is imperative to assess the dosing patterns of NP to gain insights into how well these medications meet patients’ needs, and whether the current dosing recommendations are being followed in real-world practice [ 18 ].

In this multicenter, retrospective, observational study, we aim to evaluate the real-world treatment pattern of Chinese patients with DPNP and CIPN to further address the current unmet needs for clinical decision-making, optimize treatment algorithms, and ultimately enhance the quality of care.

Methods

Study Objectives

Primary Objective

The primary objective is to describe the demographics, clinical characteristics, and treatment patterns (Supplementary Tables S1 and S2 ) among patients with DPNP and CIPN in China. The treatment pattern contents are as below: Types and proportion of treatment regimens, including index regimens and post-index regimens Treatment discontinuation/switching/add-on Restarting after discontinuation Duration of index regimen Time to treatment add-on

Secondary Objectives

The secondary objective is to investigate the dosing patterns of the key medications in index regimen for DPNP and CIPN with the following indicators: Initial daily dose Maximum daily dose Time to the maximum daily dose Proportion of patients who underwent the daily dose modification

Exploratory Objectives

The exploratory objective is to investigate the real-world adherence of index regimens for DPNP and CIPN with the following indicators: Real-world time to treatment discontinuation Real-world time to treatment switching Real-world time to treatment add-on Proportion of days covered (PDC) of the targeted medication

Additional exploratory objectives for DPNP or CIPN are as follows: For DPNP treatment-naïve patients with specific medications (Supplementary Table S1 ), the study will explore the real-world clinical effectiveness, as well as the differences in treatment patterns before and after the volume-based procurement (VBP) of pregabalin. Real-world effectiveness, including relief, alleviation, or no improvement in pain symptoms. The treatment patterns for patients with different periods of index dates, the cutoff date of which is April 30, 2021. For patients with CIPN, the study will explore chemotherapy-related risk factors and treatment behavior. Chemotherapy regimen or agents resulting in the onset of CIPN. Time from the initiation of chemotherapy to the earlier date of CIPN diagnosis or onset of CIPN symptoms. Time from the earlier date of CIPN diagnosis or onset of CIPN symptoms to index date. Real-world effectiveness of CIPN measured by Common Terminology Criteria for Adverse Events (CTCAE); pain relief, no improvement or worsening by visual analog scale (VAS), or numeric rating scale (NRS).

Study Design

This Real-World Pharmacological Treatment Pattern of Neuropathic Pain in China: A Retrospective, Database, Multicenter Study (ReTARdant, NCT06546202 ) will be conducted on a total of 600 patients with DPNP and 400 patients with CIPN from about 10 tertiary hospitals in China using leveraging electronic medical record (EMR).

The design diagram of this study is shown in Fig. 1 . The study period was from January 1, 2017 to December 31, 2022, which includes the enrollment period, pre-enrollment period, and observation period. The enrollment period is considered from January 1, 2018 to December 31, 2021. The index date is defined as the day when patients initially received index regimen with the diagnosis of DPNP or CIPN during the enrollment period. We established the pre-enrollment period as 12 months before the index date, in the range from January 1, 2017 to January 1, 2018. The observation period is defined as the period from the index date to the end of the study data collection for at least 12 months from January 1, 2018 to December 31, 2022. Fig. 1 Study design

Patients will be enrolled in accordance with inclusion and exclusion criteria of DPNP and CIPN separately as shown in Table 1 . The recruitment of patients is from both general hospitals and oncology-specialized hospitals across different regions or provinces of China to reflect the overall treatment pattern of Chinese patients. Table 1 Study eligibility criteria of patients with DPNP and CIPN Patients with DPNP Patients with CIPN Inclusion criteria 1. Patients diagnosed with diabetic neuropathy and who presented with pain between January 1, 2018 and December 31, 2021 1. Patients with neuropathy induced by the chemotherapy between January 1, 2018 and December 31, 2021, regardless of the presence of pain symptoms (chemotherapy agents were described in Supplementary Table S3 ) 2. Patients who received at least one targeted medication (described in Supplementary Table S1 ) between January 1, 2018 and December 31, 2021 2. Patients who received at least one targeted medication (described in Supplementary Table S2 ) between January 1, 2018 and December 31, 2021 3. Patients aged ≥ 18 years on the index date 3. Patients aged ≥ 18 years on the index date 4. Patients with at least one medical visit record within 12 months after the index date 4. Patients who had at least one medical visit record within 12 months after the index date Exclusion criteria Patients diagnosed with epilepsy, schizophrenia, or bipolar disorder before or on the index date 1. Patients diagnosed with epilepsy, schizophrenia, or bipolar disorder before or on the index date 2. Patients with neuralgia or neuropathy caused by tumor metastasis or non-chemotherapy-induced factors (e.g., radiotherapy, myasthenia gravis syndrome, paraneoplastic syndrome, direct tumor invasion, local tissue compression, postoperative traumatic pain, immune therapy-related pain, comorbidity-induced pain) CIPN chemotherapy-induced peripheral neuropathy, DPNP diabetic peripheral neuropathic pain

Outcome Assessment

Primary Endpoints

The primary endpoints of the study include the patient demographics and clinical characteristics as well as treatment patterns of the treatment regimens. The treatment patterns include the proportion of patients receiving different treatment regimens, the proportion of patients who discontinue/switch/add-on treatment and related medication categories, the proportion of patients who restarted treatment after discontinuation, the duration of the current treatment, and the time to treatment add-on. Treatment regimen: regimen will be evaluated and confirmed as monotherapy or combination therapy on the basis of prescription records at each visit. Monotherapy is defined as patients receiving only one targeted medication, and combination therapy is defined as patients receiving more than one targeted medication at the same time (Supplementary Tables S1 and S2 ). Treatment discontinuation: the treatment is considered discontinued when the following time interval is 90 days or more: (a) between two adjacent treatment regimens, (b) between the end of the last treatment regimen and the study end date (December 31, 2022), (c) between the end of the last treatment regimen and the date of death. Treatment switching: defined as the change of treatment regimen, either in monotherapy or in combination (excluding treatment add-on). If the treatment regimen remains the same across multiple consecutive visits, a treatment switch will not be considered. Treatment add-on: the addition of at least one targeted medications to an existing treatment regimen (monotherapy or combination therapy). Proportion of patients who restarted treatment after discontinuation : defined as among those who had discontinued treatment, the proportion of patients who received at least one targeted medication at the next visit, wherein the treatment regimen containing the targeted medication includes the same treatment medication before discontinuation or a different treatment medication after treatment switch/add-on. Duration of index regimen: defined as the time from the index date to the end of index regimen. The end of index regimen refers to the discontinuation date; for patients who did not discontinue index regimen, the end of treatment date is used. Time to treatment add-on : defined as among those who had add-on treatment, the time from the end date of the index regimen (including days covered by takeaway medications) to the start date of the add-on treatment.

Secondary Endpoints

The secondary endpoints are to investigate the dosing patterns, including the initial/maximum daily dose, time to the maximum daily dose, and proportion of patients who underwent the daily dose modification. Initial daily dose : defined as the daily dose of the first prescribed targeted medication (Supplementary Tables S1 and S2 ). Maximum daily dose : defined as the maximum of the daily dose. Time to the maximum daily dose : defined as the time interval between the initial daily dose and the maximum daily dose. Proportion of patients who underwent the dose change : defined as the proportion of patients who had the dose change (daily dose) by every visit (2, 4, and 6 weeks) after enrollment. Patients who are taking medication with a changed dosage (either increase or decrease in the daily dose) will be identified.

Exploratory Endpoints

The exploratory endpoints associated with the real-world adherence to the targeted medications for DPNP and CIPN are real-world time to treatment discontinuation/switch/add-on, and PDC of the target medications. Real-world time to treatment discontinuation : defined as the time from the index date to the date of index regimen discontinuation. Real-world time to treatment switching : defined as the time from the index date to the start date of the treatment switch (excluding treatment add-on). Real-world time to treatment add-on: defined as the time from the index date to the start date of treatment add-on. PDC : calculated as the percentage of the estimated number of days covered by the current treatment regimen within 3 months (90 days), 6 months (183 days), and 12 months (365 days). Definition of adherence: PDC < 20% is defined as no adherence; 20% ≤ PDC < 50% is defined as low adherence, 50% ≤ PDC < 80% is defined as partial adherence, and PDC ≥ 80% is defined as high adherence. The estimated number of days covered by treatment include the following: for outpatient/emergency room (ER) patients, it is calculated using the daily dose and quantity of takeaway medications prescribed to patients. For inpatient patients, it is estimated on the basis of the time interval between the start date and the end date of the prescription during the hospitalization. For those who did not have the prescription end date recorded, the discharge date will be considered as the end date, considering the quantity of takeaway medications prescribed to patients at discharge as well.

Statistical Analysis

Sample Size Estimation

The analysis will be descriptive, and no hypothesis testing will be tested. The sample size and power estimations will focus on the precision of the estimates, which is the half-width of the 95% confidence interval (CI). As shown in Table 2 , the sample sizes are demonstrated with the proportions of the most common treatment regimens and the precisions. Table 2 Estimation of the sample sizes considering the precision and assumed proportion of the most common treatment regimen Proportion of the most common treatment regimen Estimated proportion (sample size) 5% precision N = 400 N = 500 N = 600 N = 700 20% 3.9% 3.5% 3.2% 3.0% n = 246 30% 4.5% 4.0% 3.7% 3.4% n = 323 40% 4.8% 4.3% 3.9% 3.6% n = 369 50% 4.9% 4.4% 4.0% 3.7% n = 385 60% 4.8% 4.3% 3.9% 3.6% n = 369

Assuming the proportion of the most common index regimen is 50% and precision is controlled within ± 5%, a sample size of 600 patients with DPNP and 400 patients with CIPN is estimated.

The final sample size will depend on the accurate number of people who meet the inclusion and exclusion criteria.

Analysis Population

All patients who meet the inclusion and exclusion criteria will be included in full analysis set (FAS) and will be analyzed.

Demographics and Baseline Characteristics

Descriptive analysis will be mainly used for this study. Categorical variables will be described using absolute and relative frequencies. Continuous variables will be described using arithmetic mean (mean), standard deviation (SD), median, first quartile (Q1), third quartile (Q3), minimum (min), and maximum (max). Meanwhile, the number of missing variables will be reported for each variable and will not be imputed unless otherwise specified.

Primary and Secondary Endpoints Analysis

Descriptive analysis will be conducted to summarize the treatment patterns in patients with DPNP and CIPN ( n , mean, SD, median, Q1, Q3, min, and max for continuous variables; n [%] for categorical variables). Summary tables and Sankey diagrams will be used to demonstrate treatment discontinuation/switching/add-on by visits.

Exploratory Endpoint Analysis

Time-to-event variables, real-world time to treatment discontinuation, real-world time to treatment switching, and real-world time to treatment add-on will be estimated using the Kaplan–Meier method with the number of patients, number of events, number of censoring, median survival time, and its 95% CI.

Subgroup Analysis

The subgroup analysis will be conducted in addition to the main analyses mentioned above. The preliminary plan for subgroup analysis is discussed in the sections below. The subgroup variables or the subgroup categories are subject to change based on the real-data condition.

Subgroup Analyses for DPNP

Subgroup variables for DPNP will include treatment-naïve patients versus previously treated patients, age groups (< 65 years vs ≥ 65 years), duration of diabetes (< 10 years vs ≥ 10 years), treatment-naïve patients treated with specific agent (pregabalin, gabapentin, duloxetine, venlafaxine, or amitriptyline) or not, and pre-VBP versus post-VBP of pregabalin with cutoff date as April 30, 2021.

Subgroup Analyses for CIPN

Subgroup variables for CIPN will include treatment-naïve patients versus previously treated patients, top three cancer types in patients with CIPN, and CTCAE grade at index date (grade 1, grade 2, and grade ≥ 3).

Bias

Inherent limitations are introduced as a result of the study design and data sources in this study. Hospital EMR data generated from clinical practice offer possible solutions to conduct the real-world study. However, the original purpose of collecting EMR data is for clinical care management rather than clinical research, leading to certain bias, such as selection bias and information bias. In this study, control for potential biases will be performed at each stage of the study.

Methods to Minimize Selection Bias

In terms of the selection bias, the geographic coverage will be considered during the selection of study hospitals and patients to reflect the diversity of patients, physicians, and clinical practices in the real world and to improve the representativeness of the sample to the target population. Furthermore, the inclusion and exclusion criteria for study subjects will be set before the data collection to reduce bias. In addition, considering the potential differences among the included hospitals, the study will summarize baseline demographic characteristics of patients from each study site (as an appendix to the results) to explore the potential selection bias and the impact of the study sample on the representativeness of the overall target population.

Methods to Minimize Other Bias

To address potential information discrepancies caused by variations in the standards, reliability, and completeness of the EMR or health information system (HIS) data across different hospitals, the study will conduct source data verification during the data collection stage to identify and correct possible errors. To control misclassification bias due to study personnel understanding or judgment errors, the study will provide specific and explicit definitions for the study groups, study endpoints, key study factors, and variables that may influence study outcomes before data collection. Meanwhile, all study personnel will be provided with standardized training.

Data Collection and Management

Data Source

This retrospective observational study will leverage data generated from routine clinical practice in hospitals recorded in the HIS, which is widely used in Chinese hospitals as an EMR information management system, which contains all the information related to patients’ diagnosis and treatment process, including basic patient information, disease symptoms, medical history, diagnosis, disease stage, laboratory tests, imaging examination, treatment history, treatment effectiveness and safety information, follow-up, and survival.

Data Collection Process

Relevant data from eligible patients, including demographic information, clinical characteristics, treatment, and clinical outcomes, will be retrospectively collected. In line with the patient privacy protection principles, all study data will be anonymous, removing any personal identifiers that may lead to an individual patient being identified when used alone or in combination with other information.

Data Management

The contract research organization (CRO) delegated by the sponsor will be responsible for data collection and analysis. Upon hospital approval, relevant data will be collected from the HIS per protocol. The data management plan will be prepared, and logic checks will be applied during the data collection process to ensure data quality. Trained researchers will conduct further reviews of extracted data from each hospital to ensure consistency with the study standard.

Discussion

The chronic nature and diverse treatment responses of NP, particularly DPNP and CIPN, present a significant challenge in clinical management. Understanding patient demographics, clinical characteristics, and treatment patterns is crucial for optimizing management strategies and improving patient outcomes. However, comprehensive studies addressing these aspects, specifically in the Chinese population, are limited, necessitating the need for the current study.

The ReTARdant study is the first large, retrospective study leveraging EMR data with a national representative population of Chinese patients with DPNP and CIPN. Existing literature predominantly reports findings from the Western population, which may not capture the unique characteristics and responses to the treatment in Chinese patients with DPNP and CIPN (Table 3 ). The present study aims to enroll 600 patients with DPNP and 400 with CIPN. This sample size is notably larger compared with other studies that reported DPNP treatment patterns, such as studies by Kim et al. ( n = 577) [ 19 ], Jana et al. ( n = 232) [ 20 ], and Lian et al. ( n = 401) [ 15 ], with each study having fewer patients, and a limited scope of analysis. However, the PDN-Scope study enrolled a higher number of patients ( n = 1547) compared with our study [ 14 ]. Furthermore, our study features a significantly larger sample size for assessing CIPN treatment patterns compared with previous studies by Selvy et al. (67 patients) [ 21 ] and Hiramoto et al. (283 patients) [ 22 ], but a smaller sample size than a Japanese study including 4739 patients [ 23 ]. Table 3 ReTARdant study design compared with similar database studies ReTARdant study PDN-Scope study [ 14 ] Kim et al. [ 19 ] Lian et al. [ 15 ] Jana et al. [ 20 ] Yokoyama et al. [ 23 ] Hiramoto et al. [ 22 ] Selvy et al. [ 21 ] Number of patients enrolled 600 patients with DPNP and 400 with CIPN to be enrolled 1547 patients with DPNP 1338, of which 577 (43.1%) were diagnosed with DPNP 401 patients with DPN 232 patients with DSPN; of which, 158 with DPNP 4739 patients treated with oxaliplatin; of which, 759 patients received medication for CIPN 283 patients with breast or gynecological cancer who underwent paclitaxel-based chemotherapy 67 patients treated with bortezomib-based chemotherapy for MM Country China China (Chinese Mainland) Korea China USA Japan Japan France Characteristics evaluated Patient demographics, clinical characteristics, and treatment patterns, dosing patterns and real-world medications adherence information of DPNP and CIPN in China Participants’ demographics, medical histories, glucose parameters, DN4 scores, VAS pain scores, PHQ-9 scores, GAD-7 scores, and therapies Participants’ demographics, medical histories, BPI-SF, MOS-Sleep Scale, EQ-5D, and VAS pain scores Participants' demographics, medical history, analgesic use, MNSI, NRS pain score, PHQ-9 score, GAD -7 score, QoL score (SF-12), and diabetes treatment status Participants’ demographics, medical histories, laboratory tests, neurological examination, quantitative sensory testing, nerve conduction studies, and neuropathy severity scores Patients’ demographics, medical history, duration of oxaliplatin treatment, number of drugs used for CIPN treatment, association between CIPN medication and duration of oxaliplatin treatment, proportion of patients who received CIPN medication Patients’ demographics, medical history, risk factors for PIPN, and ongoing prescription drug use for PIPN Participants' demographics, medical history, sensory score, motor and vegetative scores of the QLQ-CIPN20, VAS pain scores, DN4 scores, history of neuropathy and neuropathic pain, ongoing pain medications, and HRQoL Patients who received prescription for neuropathic pain To be evaluated 19.52% (302/1547) 387 (69.5%) were taking medication for current pain in patients with DPNP 132 patients reported using analgesics, and 221 patients reported not using analgesics Of 158 patients with DSPN, 70 patients were treated with standard analgesics whereas 88 subjects received either non-recommended analgesic or no treatment Of the 4739 patients with a duration of oxaliplatin treatment of ≤ 13 months, 759 (16.0%) received CIPN medication Of the 283 enrolled patients, 124 (43.8%) received prescription of one or more CIPN medication 52.0% (35/67) of all patients analyzed and 66.7% (12/18) of patients with a sensory CIPN received pain medications Most widely used pharmacological treatment To be evaluated Gabapentin 62.86%; pregabalin 12.57%; duloxetine 9.14%; ibuprofen 3.14%; amitriptyline 2.57% TCA 26%; anticonvulsants 41.94%; SSRI 1.21%; topical preparations 0.17%; opioids 1.39%; SNRI 2.08% Pregabalin was the first choice for patients (69.7%), followed by duloxetine and tapentadol Pregabalin 19.8%; gabapentin 14.2%; TCA 9.4%; SNRI 7.5%; tramadol 7.5%; opioids 5.7%; NSAIDs 21.7%; clonazepam 6.6% Any pain-related medication 91.4%; opioids 82.7%; anticonvulsants 48.2%; NSAIDs 38%; and antidepressants 20.9% Gosha-Jinki-Gan 7.6%; pregabalin 4.8%; duloxetine 2.1% Pregabalin mecobalamin or Gosha-Jinki-Gan 20 to − 30%; duloxetine 14% Paracetamol was the most widely used in patients with sensory CIPN (75%) and neuropathic pain (62.5%) One patient each with sensory CIPN received gabapentin and pregabalin; no patient received duloxetine BPI-SF Brief Pain Inventory–Short Form, CIPN chemotherapy-induced neuropathic pain, DN4 Douleur Neuropathique 4 Questionnaire, DPN diabetic peripheral neuropathy, DPNP peripheral diabetic neuropathic pain, DSPN diabetic distal symmetrical sensory-motor polyneuropathy, EQ-5D EuroQol-5 dimension, GAD-7 generalized Anxiety Disorder 7, HRQoL health-related quality of life, MM multiple myeloma, MNSI Michigan Symptom Score, MOS-Sleep Medical Outcomes Study Sleep, NRS numerical rating scale, NSAID non-steroidal anti-inflammatory drug, PHQ-9 Patient Health Questionnaire 9, PIPN paclitaxel-induced peripheral neuropathy, QLQ-CIPN20 Quality of Life Questionnaire to Assess Chemotherapy-Induced Peripheral Neuropathy, QoL quality of life, SF-12 Short Form 12 Health Survey, SNRI serotonin-norepinephrine reuptake inhibitor, SSRI selective serotonin reuptake inhibitor, TCA tricyclic antidepressant, VAS visual analog scale

In the study by Kim et al., the prevalence of DPNP in patients with diabetic peripheral neuropathy and the baseline characteristics of patients were evaluated. The risk factors and the clinical impact associated with DPNP were also studied using various pain scale measures. Of the patients with DPNP, 69.5% of patients taking medication for current pain had lower pain scores than those not taking medications [ 19 ]. Similarly, Jana et al. conducted a cross-sectional observational study evaluating the severity of NP, analgesic use, and sensory phenotypes in patients with diabetic distal symmetrical sensory-motor polyneuropathy (DSPN) [ 20 ]. Apart from reporting the demographic characteristics and pain scores, a study by Lian et al. investigated the status of analgesic use in patients with DPNP in China. Specifically, the study evaluated the commonly used analgesics, patient satisfaction, pain relief, economic burden, and QoL after analgesic use. Pregabalin was found to be the most preferred, and opioids were the least used analgesic in China. Moreover, patients receiving analgesics and who previously received analgesics reported lower pain scores, an improved QoL when compared with those not using analgesics, and the satisfaction rate of efficacy was 46.18% [ 15 ]. The PDN-Scope study on mainland China reported patient demographics, pain severity, and pain scores (VAS) and explored pharmacological treatment patterns in patients with DPNP [ 14 ]. Regarding studies reporting CIPN treatment patterns, the study by Selvy et al. only reported the proportion of patients who underwent pharmacological treatment in addition to their demographic characteristics and pain scores [ 21 ]. Yokoyama et al. reported the proportion of patients who received CIPN medication, number of drugs used for CIPN treatment, and the association between CIPN medication and duration of oxaliplatin treatment [ 23 ]. Furthermore, Hiramoto et al. reported the risk factors and ongoing prescription drug use for CIPN [ 22 ]. In contrast to these studies, the ReTARdant study will collect comprehensive data on treatment patterns, including detailed information on drug flow, discontinuation rates, drug switching, drug add-ons, dosage variations, and the PDC. These additional parameters allow for a deeper understanding of treatment dynamics and offer potential insights into the real-world treatment practices and patient behavior for DPNP and CIPN in China.

Currently, the most common clinical drug therapy for NP involves ion channel drugs, for which the response rate is only about 46.3% [ 24 ], varying with the underlying causes of NP [ 25 ]. The PDN-Scope study reported gabapentin to be the most widely used treatment by the patients with DPNP (62.8%), followed by pregabalin (12.57%) and duloxetine (9.14%) [ 14 ]. Furthermore, Jana et al. reported that of the 158 patients with DPNP, 70 patients were treated with standard analgesics, with (NSAIDs) being the most commonly used (21.7%), followed by pregabalin (19.8%) [ 20 ]. In a study by Xiao et al. among Chinese patients, 78.72% of the patients interviewed had an intention to receive pain medications. However, 40.11% of the patients who refused pain management had a fear of opioids addiction and the adverse effect of analgesics, which suggested the lack of education in pain management, patient concerns about cost, poor patient adherence, and patients’ fear of addiction to opioids are common barriers to effective pain management [ 26 ]. Our study aims to explore the proportion of patients receiving various treatment regimens, which will provide insights into the current treatment practices of DPNP and CIPN in China. Specifically, commonly prescribed drugs such as TCAs, SNRIs, calcium channel ligands, sodium channel blockers, NSAIDs, opioids, and drugs for neuropathy will be focused upon in this study. By understanding the distribution of treatment choices, we will evaluate therapies that are favored for certain patient subgroups and factors that influence these decisions.

Our study will analyze dosing patterns of the targeted medications for DPNP and CIPN including daily dose and maximum daily dose, time to achieve the daily dose, and dose adjustments frequency. It will also evaluate the proportion of patients with changes in daily dose. In a head-to-head comparison of dosing patterns of duloxetine and pregabalin, the mean initial daily dose was 54.3 mg for duloxetine and 171.8 mg for pregabalin. Moreover, individuals initiating pregabalin generally began treatment with a low dose, but a significant number either increased their daily doses up to 264 mg over time or opted to discontinue the medication [ 27 ]. The importance of standardized treatment in clinical practice will be highlighted through dosing pattern evaluation.

Adherence to prescribed medications is a crucial factor influencing treatment success in NP management. Despite the effectiveness of pain medicines, approximately 40% of the prescription medicines are not taken as prescribed [ 28 ]. Adherence to duloxetine of 29.9% and adherence to TCAs of 66% in patients with NP were determined by urinary analysis [ 29 ]. Furthermore, in a study conducted by Zhao et al., an adherence rate of 58.9% to analgesics was observed in Chinese patients with cancer pain. Moreover, adherence was associated with pain duration of longer than 3 months and the presence of NP, among other factors [ 30 ]. By studying the exploratory objectives such as real-world data on treatment discontinuation, switching, add-on, and the PDC by medications, we aim to identify barriers to medication adherence and strategies to improve adherence of patients with DPNP and CIPN in China. Results from this study can offer insights into associations among drug adherence, insufficient response to initial therapy, and side effects leading to improved routine care and guideline development.

Strength and Limitations

To our knowledge, this is the first large-sample, multicenter, retrospective study to investigate the real-world treatment patterns and outcomes in Chinese patients with DPNP and CIPN observed between January 2018 and December 2022. Therefore, this study is expected to reflect current real-world treatment patterns and outcomes. We expect that this study will provide profound insights into clinical unmet needs of DPNP and CIPN, especially potential treatment gaps between clinical practice and guidelines in China, by evaluating the treatment patterns.

The present study does have certain limitations. Firstly, as a retrospective observational study, these analyses results will descriptively analyze rather than explore causation, and hence all conclusions should be cautiously interpreted. Secondly, data availability is limited because of accessible information recorded in hospital EMR and the absence of long-term follow-up and therefore may introduce selection bias and missing data. However, this method is optimal and practicable to address the target research questions, especially with the large sample size and geographic representative data. Moreover, variations in clinical practice and medical record-keeping across different hospital types and among physicians in China could increase data heterogeneity and reflect real-world practice, especially for DPNP and CIPN diagnosis.

Conclusion

This study will address a critical need for detailed characterization of DPNP and CIPN, patient profiles, treatment patterns, medication dosing, and adherence in China. By elucidating these factors, we aim to contribute substantial evidence to the field in ultimately guiding clinicians in making informed decisions tailored to the needs of Chinese patients with NP.

Supplementary Information

Below is the link to the electronic supplementary material. Supplementary file1 (PDF 145 KB)

Qi Pan, Xiaoyu Zhai, and Haining Wang contributed equally to this manuscript.

Acknowledgements

We thank the participants of the study.

Medical Writing, Editorial, and Other Assistance

The authors would like to acknowledge Natasha Naval Agarwal, PhD, Priyanka Bannikoppa, PhD, and Roopa Subbaiah, PhD of Indegene Ltd., Bangalore, India for editorial support which was funded by Daiichi Sankyo (China) in accordance with the Good Publication Practice guidelines.

Author Contributions

Substantial contributions to the conception or design of the work: Bifa Fan, Jun Zhao, Lixin Guo; agreement to be accountable for sectional aspects of the work in ensuring that questions related to the accuracy or integrity of the work are appropriately investigated and resolved: Bifa Fan, Jun Zhao, Lixin Guo, Qi Pan, Xiaoyu Zhai, Haining Wang, Jianling Du, Yanxia Shi, Xuefeng Yu, Sunjie Yan, Xiaohong Wu, Hui-hui Li, and Tao Sun; drafting the work or revising it critically for important intellectual content: Qi Pan, Xiaoyu Zhai, Haining Wang, Bifa Fan, Jun Zhao and Lixin Guo. All named authors meet the International Committee of Medical Journal Editors (ICMJE) criteria for authorship for this article, take responsibility for the integrity of the work as a whole, and have given their approval for this version to be published.

Funding

This study and the journal’s Rapid Service Fee was funded by Daiichi Sankyo (China) Holdings Co., Ltd, Shanghai, China.

Data Availability

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

Declarations

Conflict of Interest

This study was funded by Daiichi Sankyo (China). All authors (Qi Pan, Xiaoyu Zhai, Haining Wang, Jianling Du, Yanxia Shi, Xuefeng Yu, Sunjie Yan, Xiaohong Wu, Hui-hui Li, Tao Sun, Lixin Guo, Jun Zhao, Bifa Fan) declare no other conflict of interest and have nothing to disclose.

Ethics/Ethical Approval

The study will be performed in accordance with the principles stated in the Declaration of Helsinki of 1964 and its later amendments. Ethical approval from leading hospitals was obtained from the China-Japan Friendship Hospital ethics committee (2024-KY-131) and Beijing Cancer Hospital ethics committee (2024YW107); the collaborating hospitals obtained local approval (Supplementary Tables S4 ). As a result of all patient data being collected retrospectively, written informed consent from patients was waived by the ethics committee. The results will be published in academic journals and presented at national and international academic conferences.

Patient and Public Involvement

Patients and/or the public were not involved in the design, conduct, reporting, or dissemination plans of this research.

Patient Consent for Publication

Not applicable.

Trial Status

This is version 1.2 of the protocol, dated December 18, 2024. Data collection is ongoing and expected to be completed by September 2025.

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